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Structure-preserving Sparse Identification of Nonlinear Dynamics for
  Data-driven Modeling

Structure-preserving Sparse Identification of Nonlinear Dynamics for Data-driven Modeling

11 September 2021
Kookjin Lee
Nathaniel Trask
P. Stinis
ArXivPDFHTML

Papers citing "Structure-preserving Sparse Identification of Nonlinear Dynamics for Data-driven Modeling"

18 / 18 papers shown
Title
Equilibrium Conserving Neural Operators for Super-Resolution Learning
Equilibrium Conserving Neural Operators for Super-Resolution Learning
Vivek Oommen
Andreas E. Robertson
Daniel Diaz
Coleman Alleman
Zhen Zhang
Anthony D. Rollett
George Karniadakis
Rémi Dingreville
33
1
0
18 Apr 2025
Efficiently Parameterized Neural Metriplectic Systems
Efficiently Parameterized Neural Metriplectic Systems
Anthony Gruber
Kookjin Lee
Haksoo Lim
Noseong Park
Nathaniel Trask
58
1
0
28 Jan 2025
Generalizing the SINDy approach with nested neural networks
Generalizing the SINDy approach with nested neural networks
Camilla Fiorini
Clément Flint
Louis Fostier
Emmanuel Franck
Reyhaneh Hashemi
Victor Michel-Dansac
Wassim Tenachi
68
1
0
28 Jan 2025
Learning Physics From Video: Unsupervised Physical Parameter Estimation for Continuous Dynamical Systems
Learning Physics From Video: Unsupervised Physical Parameter Estimation for Continuous Dynamical Systems
Alejandro Castañeda Garcia
J. C. V. Gemert
Daan Brinks
Nergis Tömen
31
0
0
02 Oct 2024
Symmetry-Informed Governing Equation Discovery
Symmetry-Informed Governing Equation Discovery
Jianke Yang
Wang Rao
Nima Dehmamy
Robin G. Walters
Rose Yu
34
0
0
27 May 2024
AI-Lorenz: A physics-data-driven framework for black-box and gray-box
  identification of chaotic systems with symbolic regression
AI-Lorenz: A physics-data-driven framework for black-box and gray-box identification of chaotic systems with symbolic regression
Mario De Florio
Ioannis G. Kevrekidis
George Karniadakis
41
15
0
21 Dec 2023
Interpretable Neural PDE Solvers using Symbolic Frameworks
Interpretable Neural PDE Solvers using Symbolic Frameworks
Yolanne Yi Ran Lee
AI4CE
24
0
0
31 Oct 2023
Correcting model misspecification in physics-informed neural networks
  (PINNs)
Correcting model misspecification in physics-informed neural networks (PINNs)
Zongren Zou
Xuhui Meng
George Karniadakis
PINN
16
40
0
16 Oct 2023
Coarse-Graining Hamiltonian Systems Using WSINDy
Coarse-Graining Hamiltonian Systems Using WSINDy
Daniel Messenger
J. Burby
David M. Bortz
38
6
0
09 Oct 2023
Reversible and irreversible bracket-based dynamics for deep graph neural
  networks
Reversible and irreversible bracket-based dynamics for deep graph neural networks
A. Gruber
Kookjin Lee
N. Trask
AI4CE
25
9
0
24 May 2023
Pseudo-Hamiltonian system identification
Pseudo-Hamiltonian system identification
Sigurd Holmsen
Sølve Eidnes
S. Riemer-Sørensen
15
3
0
09 May 2023
Mining Causality from Continuous-time Dynamics Models: An Application to
  Tsunami Forecasting
Mining Causality from Continuous-time Dynamics Models: An Application to Tsunami Forecasting
Fan Wu
Sanghyun Hong
Dobsub Rim
Noseong Park
Kookjin Lee
AI4TS
29
1
0
10 Oct 2022
Parameter-varying neural ordinary differential equations with
  partition-of-unity networks
Parameter-varying neural ordinary differential equations with partition-of-unity networks
Kookjin Lee
N. Trask
22
2
0
01 Oct 2022
Interpretable Polynomial Neural Ordinary Differential Equations
Interpretable Polynomial Neural Ordinary Differential Equations
Colby Fronk
Linda R. Petzold
19
26
0
09 Aug 2022
Pseudo-Hamiltonian Neural Networks with State-Dependent External Forces
Pseudo-Hamiltonian Neural Networks with State-Dependent External Forces
Sølve Eidnes
Alexander J. Stasik
Camilla Sterud
Eivind Bøhn
S. Riemer-Sørensen
11
17
0
06 Jun 2022
Gaussian processes meet NeuralODEs: A Bayesian framework for learning
  the dynamics of partially observed systems from scarce and noisy data
Gaussian processes meet NeuralODEs: A Bayesian framework for learning the dynamics of partially observed systems from scarce and noisy data
Mohamed Aziz Bhouri
P. Perdikaris
18
20
0
04 Mar 2021
Lagrangian Neural Networks
Lagrangian Neural Networks
M. Cranmer
S. Greydanus
Stephan Hoyer
Peter W. Battaglia
D. Spergel
S. Ho
PINN
121
419
0
10 Mar 2020
Symplectic Recurrent Neural Networks
Symplectic Recurrent Neural Networks
Zhengdao Chen
Jianyu Zhang
Martín Arjovsky
Léon Bottou
139
219
0
29 Sep 2019
1